Short-Term and Long-Term Impacts of Genetic Discovery on the

5/15/2015
Short-term and long-term impacts
of genetic discovery
on the practice of endocrinology
Joel Hirschhorn, MD, PhD
Center for Basic and Translational Obesity Research
Division of Endocrinology
Boston Children’s Hospital/Harvard Medical School
Broad Institute
Disclosure
• Grant from Pfizer
• No impact on presentation
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5/15/2015
Why study human genetics?
• Genetics reveals biological causes for
human disease
guides new treatments
Long Term Impact
• Genetics can help provide diagnosis or
predictive information to patients
Short Term Impact
Why study human genetics?
• Genetics reveals biological causes for
human disease
guides new treatments
Long Term Impact
• Genetics can help provide diagnosis or
predictive information to patients
Short Term Impact
2
5/15/2015
“Genetic disease”
the Mendelian model
Disease
Gene
Examples include:
Sickle Cell Disease, Cystic Fibrosis, MODY, etc.
Rare mutations can cause
severe obesity syndromes
SIM1
MC4R
TRKB
PCSK1
POMC
BDNF
SH2B1
LEPR
LEP
Montague et al. Nature 1997
Jackson et al. Nature Genetics 1997
Strobel et al. Nature 1998
Clement et al. Nature 1998
Krude et al. Nature Genetics 1998
Yeo et al. Nature Genetics 1998
Vaisse et al. Nature Genetics 1998
Farooqi et al. JCI 2000
Vaisse et al. JCI 2000
Yeo et al. Nature Neuroscience 2004
Hung et al. Int J Obesity 2007
Ahituv et al. Am J Hum Genet 2007
Gray et al. Diabetes 2006
Han et al. New Engl J Med 2008
Bochukova et al. Nature 2010
Walters et al. Nature 2010
And others…
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5/15/2015
Known genes for Mendelian
obesity
• Leptin to the hypothalamus and BDNF
– LEP, LEPR, MC4R, POMC, SIM1, PCSK1,
BDNF, NTRK2
• Prader-Willi syndrome (PWS), Ciliopathies
and other syndromic genes
– Exact causal gene(s) not known for PWS
– Many genes for Bardet Biedl syndrome (BBS)
– Genes for a variety of other syndromes
• GNAS, ALMS1, VPS13B, PHF6, RAB23, CEP19,
RAI1, TBX3, KSR2
www.omim.org
Leptin deficiency
• Low leptin levels
• Very rare
• Hypogonadism
• Variable T cell defects
• Treat with leptin
From Farooqi et al., JCI 2002
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5/15/2015
Bio-inactive leptin
Leptin level high
(42.6 ng/mL)
From Wabitsch et al.
New Engl J Med 2015
MC4R
• Encodes a receptor for -MSH critical for
regulation of appetite and energy balance
• The gene most frequently observed to be
mutated in severe early-onset obesity
–
–
–
–
–
~1-2% of patients undergoing RYGB
Binge eating
Hyperinsulinism
Subtle tall stature
BP tends to be lower
Farooqi et al. NEJM 2003
Sayk et al. JCEM 2010
Hatoum et al. JCEM 2012
Hainerova and Lebl World Rev Nutr Diet 2013
Meehan et al. Mamm Genome 2006
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POMC
• Encodes proopiomelanocortin
• Alpha MSH
– Obesity
– Red hair
• ACTH
– Adrenal insufficiency
From Krude et al., Nat Genet 2002
SH2B1
• Involved in leptin signaling
• Near an an autism locus
• Some patients with obesity
(sometimes with autism)
have SH2B1 deletions
Ren et al. JCI 2007
Bochukova et al. Nature 2010
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5/15/2015
BDNF
• Contiguous gene deletion
• Aniridia, Wilm’s tumor,
genitourinary
malformations, intellectual
disability
BDNF deleted
BDNF intact
Han et al., New Engl J Med 2008
Prader Willi Syndrome
• Imprinted disorder, gene(s)
unknown
• Dysmorphic features
• Decreased movement during
pregnancy
• Initial hypotonia and failure to
thrive, then hyperphagia
(often severe)
• Hypogonadism
• Intellectual disability
• Sleep apnea
• Other features
Cassidy et al. Genet Med. 2012
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5/15/2015
Bardet-Biedl syndrome
and related ciliopathies
• Many (~20 known) genes can cause the disease
• Genes encode components of the primary cilium
• Associated features are highly variable
– Renal anomalies
– Retinal degeneration
– Cognitive impairment
– Polydactyly
– Male hypogenitalism
– Other features
Other genetic obesity syndromes
• Several others recognized
–
–
–
–
–
–
Albright hereditary osteodystrophy
Alstrom syndrome
Borjeson-Forssman-Lehmann syndrome
Carpenter syndrome
Morbid obesity and spermatogenic failure
Smith-Magenis Syndrome
• Often have reproductive/gonadal/genital
issues, retinal disease, short stature,
neurobehavioral issues, and/or limb
abnormalities
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Many other
Mendelian endocrine disorders
• Multiple Endocrine Neoplasia
– MEN 1, MEN2A, MEN2B
– Diagnosis guides treatment and prognosis
• Hypothyroidism
– Rarely, a recessive disorder
– Diagnosis affects recurrence risk
• MODY
– Dominant, likely underdiagnosed
– Diagnosis can influence treatment
• Short stature
– Hundreds of disorders, including many skeletal
dysplasias
• Neonatal diabetes
– Diagnosis of ABCC8/KCNJ11 can influence treatment
Why recognize patients with
Mendelian disorders?
• Some patients should get treated
differently
– Leptin deficiency, MODY, for example
•
•
•
•
Counseling for relatives/reproduction
Screening for/explaining comorbidities
Diagnosis can be valuable psychologically
Enables research into whether underlying
causes should affect clinical management
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5/15/2015
How to recognize patients with
Mendelian disorders?
• Severe, Syndromic, Segregating, or too Soon
• Sometimes not easy clinically
– For obesity:
•
•
•
•
•
Family history may not be clear
MC4R mutations don’t always segregate clearly in families
Many patients have childhood onset obesity
Many don’t know or misestimate age of onset
Associated symptoms may be subtle
– For short stature:
• Assortative mating means family history is difficult
Diagnosing Mendelian Disease
• Nongenetic diagnosis
– Clinical diagnosis
– Biochemical/laboratory diagnosis
• Targeted genetic testing for diagnosis
– Single gene analysis
– Targeted sequencing (gene panel)
• Genome-wide genetic testing for diagnosis
–
–
–
–
Karyotype
Copy number variation
Exome sequencing
Genome sequencing
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Comprehensive sequencing of exons
4 patients with known
mutations in MYH3
Sequence all exons
1 gene with rare
missense variants in
all 4 patients (MYH3)
Ng et al.
Nature 2009
Exome sequencing has
revolutionized genetic discovery
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5/15/2015
Exome sequencing in the clinic
• We can now sequence full exomes for less
than it used to cost to screen one gene.
~20,000 genes
Exome sequencing for diagnosis
• 250 patients, no previous diagnoses
• Exome sequencing
• Look for known pathogenic or likely pathogenic
variants in known genes
Yang et al. New England Journal of Medicine 2013
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Exome sequencing for diagnosis
• 250 patients, no previous diagnoses
• Exome sequencing
• Look for known pathogenic or likely pathogenic
variants
in known genes
~25-50%
of patients with a high
• 66 diagnoses
in 62
mostly
neurological
suspicion
ofpatients,
a genetic
disorder
canor
Noonan syndrome
receive a diagnosis from exome
sequencing
25 de novo mutations
– 33 autosomal dominant
•
– 9 X-linked recessive
• 4 de novo mutations
– 20 autosomal recessive
• 30 patients with actionable incidental findings
Yang et al. New England Journal of Medicine 2013
Possible outcomes of exome sequencing
“Pathogenic” or “likely
pathogenic” mutation
Gene fits clinical
picture
Variant of unknown
significance
Gene sort of fits clinical
picture
Gene doesn’t fit clinical
picture
“Known” pathogenic mutations may not be fully penetrant
“Known” pathogenic mutations may not actually be pathogenic
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5/15/2015
Possible outcomes of exome sequencing
“Pathogenic” or “likely
pathogenic” mutation
Gene fits clinical
picture
Variant of unknown
significance
Gene sort of fits clinical
picture
Gene doesn’t fit clinical
picture
Interpretation is hard but improving
• Large reference databases
– Population allele frequencies
– Exome Aggregation Consortium: ~95K samples
• Improved curation of assignment of
pathogenicity
– ClinGen, ClinVar
– Others
http://exac.broadinstitute.org/
http://clinicalgenome.org/
http://www.ncbi.nlm.nih.gov/clinvar/
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Screening and incidental findings
“Incidentaloma”
endocrinesurgery.net.au
ACMG Guidelines for
return of incidental genetic findings
Green et al. Genet. Med 2013
Initial guidelines have been controversial,
and were since modified
(Responses in Genet. Med 2013 and elsewhere)
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Sequencing in short stature patients
Rare variants
with more of
an influence
Height
Sequencing in short stature patients
• ~500 families: ≥ 1 child with short stature
• No known genetic diagnoses
• Boston/Cincinnati + collaborators 50
46
40
35
28
30
26 26
25
20
20
16
15
5
9
8
10
3 2 3 2
3
0
-5
-4.75
-4.5
-4.25
-4
-3.75
-3.5
-3.25
-3
-2.75
-2.5
-2.25
-2
Andrew Dauber
Number of Probands
45
Height Z Score
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Multiple patients with new diagnoses
• Ehlers-Danlos Syndrome, Progeroid Type
– Only ever reported in <10 individuals
•
•
•
•
Two cases of 3-M Syndrome
One case of Floating Harbor Syndrome
Novel mutation in IGF1R
Two cases of Noonan Syndrome
– Implications for possible cardiac defects
• Enrichment of variants in NPR2
• 5/14 patients with ISS and height SDS < -3
Guo et al. Horm Res Pediatr 2015; Wang et al. Hum Mutation 2015
New diagnosis, but not a textbook case
SLC35C1
•
•
•
•
Two brothers, 17 and 20 years old
Short stature (-2.7 and -3.2 SDS)
Developmental delay
Other minor physical findings
Dauber et al. Hum Mol Genet 2014
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What disease is caused by
mutations in SLC35C1?
Congenital disorder of glycosylation type
2c/Leukocyte adhesion deficiency type 2
Typically presents with:
–
–
–
–
–
Short stature YES
Developmental Delay YES
Recurrent Infections NO
Specific immunological defects NO
A diagnostic blood type NO
Expected biochemical defect in fucosylation
(but not quite as severe as usual)
G0
G0F G1 G1F
G2
G2F
Proband 1
Proband 2
Sister
Mother
Father
16.00 18.00 20.00 22.00 24.00 26.00 28.00 30.00 32.00 34.00 36.00 38.00 40.00
In collaboration with Altan Ercan and Peter Nigrovic;
Other studies with Pieter Jacobs and Robert Sackstein
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Why is this diagnosis important?
• New, less severe form of a rare disease
• No chance of diagnosis without genetics
• Difficult even with clinical sequencing
– Might not get reported back to clinician
– Biochemical work key to clinching diagnosis
• Important potential therapeutic implications:
May be treatable
with a dietary supplement
Short stature, advanced bone age
Nilsson et al. J Clin Endocrinol Metab 2014
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Heterozygous mutations in ACAN
No OA
No OA
OA
Tompson et al. Am J Hum Genet 2009; Statten et al. Am J Hum Genet 2010;
Gleghorn et al. Am J Hum Genet 2005, Am J Med Genet 2011
Exome vs targeted sequencing
• Targeted testing:
– Targeted tests may be more sensitive
– Targeted tests have fewer incidental findings
– Lab MAY understand variation in targeted genes
• Exome sequencing:
– More comprehensive
– Does not rely on guessing correct gene
– Likely more cost-effective than multiple panels
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Exome vs targeted sequencing
Consider targeted testing:
– Gene panel is well-established and high yield
– Suspicion is high for genes in the panel
Consider exome sequencing (and microarray):
– Suspicion is high for genetic disorder but not a
particular gene/diagnosis
– Prior negative genetic test
Sequencing in short stature:
A possible approach
High suspicion for
Mendelian disease
Targeted
Targeted
Targeted
Targeted
Exome and
copy number
Dauber et al. JCEM 2014
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5/15/2015
Exome sequencing has
revolutionized human genetics
• Gene discovery in Mendelian disease
– Success rates are notable but variable
• Being used in diagnosis
– Efficient use of sequencing
– Relies less on guessing correct gene
– What information to look at? To report?
– Results not always definitive
– How to deal with “clinically actionable”
incidental findings (eg BRCA1)
Gilissen et al. Genome Biol. 2011, Choi et al. PNAS 2009, many others
See ACMG guidelines
Why study human genetics?
• Genetics reveals biological causes for
human disease
guides new treatments
Long Term Impact
• Genetics can help provide diagnosis or
predictive information to patients
Short Term Impact
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5/15/2015
Biomedical research and
human disease
Study
human
disease
Therapeutic
leads
Biological
insight
Biomedical research and
human disease
Human
genetics
Therapeutic
leads
Biological
insight
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5/15/2015
Causal biology in humans leads to
therapeutic opportunities
Michael Brown and Joseph Goldstein
http://www4.utsouthwestern.edu/moleculargenetics/pages/brown/past.html
Cholesterol synthesis in the liver
Statins
“Genetic disease”
the Mendelian model
Disease
Gene
Examples include:
Sickle Cell Disease, Cystic Fibrosis, MODY, etc.
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5/15/2015
Most diseases and traits are genetic, but complex
Gene 1
Gene 2
Genes
...
Gene 3
Gene N
Environment
Disease
Nutrition
Environment
in utero
Etc.
We can survey most of the genome for common
variants that influence diseases/traits
Knowledge of
common variation
Well-phenotyped
clinical samples
Genotyping
platforms
Analytic methods
and software
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5/15/2015
1000’s of genetic variants that affect human biology and disease
GWAS: mostly allele frequencies >5%
Effect of each variant: typically small
Impact of biological discovery: may be large
Some associated loci encode drug targets
Diabetes:
Sulfonylureas (KCNJ11)
Thiazolidinediones (PPARG)
Lipids:
Statins (HMGCR)
Ezetimibe (NPC1L1
PCSK9 antibodies (PCSK9)
Bone density:
Estrogens (ESR1)
RANK antagonists (RANKL)
Height:
Estrogen (ESR1)
IGF1 (IGF1R)
Aromatase inhibitors (CYP19A1)
Growth Hormone (GH1)
Many others
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New genes =
New therapeutic leads
Rarer protective alleles are informative
Zhao et al.
Am J Hum Genet
2006
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5/15/2015
Genetics of height
Height is the classical polygenic trait
Galton, 1886
Pearson and Lee, 1903
Fisher, 1918
GIANT Consortium
(Genetic Investigation of ANthropometric Traits)
DGI/MIGEN
Leif Groop
Joel Hirschhorn
Sekar Kathiresan
Guillaume Lettre
Liz Speliotes
Ben Voight
FUSION
Gonçalo Abecasis
Michael Boehnke
Karen Mohlke
Anne Jackson
Heather Stringham
Cristen Willer
CoLaus
Vincent Mooser
Dawn Waterworth
Kijoung Song
Toby Johnson
CONSORTIUM
(expansion)
EPIC, Fenland
Inés Barroso
Ruth Loos
Nick Wareham
Shengxu Li
Jian’An Luan
Eleanor Wheeler
Jing Hua Zhao
Twins UK
Tim Spector
Panos Deloukas
Massimo Mangino
Nicole Soranzo
WTCCC (UKBS, CAD, HTN, T2D, 1958BC)
Mark Caulfield
Tim Frayling
Mark McCarthy
KORA
Patricia Munroe
Erich Wichmann
Willem Ouwehand
Christian Gieger
Nilesh Samani
Iris Heid
David Strachan
Claudia Lamina
David Evans
CGEMS (NHS and PLCO)
David Hadley
Sonja Berndt
Alistair Hall
Stephen Chanock
Cecilia Lindgren
Richard Hayes
Hana Lango
David Hunter
Massimo Mangino
Frank Hu
Inga Prokopenko
Lu Qi
Joshua Randall
SardiNIA
Chris Wallace
Gonçalo Abecasis
Michael Weedon
David Schlessinger
Ele Zeggini
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GIANT Consortium
(Genetic Investigation of ANthropometric Traits)
CHARGE (AGES, Amish, deCODE
EUROSPAN (MICROS, PROCARDIS
ARIC, Family Heart Study, Kári Stefansson
Hugh Watkins
ORCADES, VIS,
Framingham, Rotterdam) Unnur Thorsteinsdottir
KORCULA, N. Sweden) Anders Hamsten
Caroline Fox
Daniel Gudbjartsson
John Peden
Harry Campbell
Kari North
Valgerdur Steinthorsdottir Igor Rudan
SEARCH
Keri Monda
Gudmar Thorleifsson
Peter Pramstaller
Paul Pharoah
Tammy Harris
Andrew Hicks
Jonathan Tyrer
Vilmunder Gudmundsson Remaining ENGAGE
(ERF, EGP, Finnish Asa Johansson
Albert Smith
SHIP
Jim Wilson
Twins, GENMETS,
Jeff O’Connell
Henry Völzke
NESDA, NFBC, NTR) ADVANCE
Ingrid Borecki
Alexander Teumer
Leena Palotie
Thomas Quertermous
Mary Feitosa
CNRS/ICL
Mark McCarthy
Tim Assimes
Shamika Ketkar
Philippe Froguel
Cornelia
van
Duijn
Joshua
Knowles
Adrienne Cupples
Christian Dina
Yuri
Aulchenko
Devin Absher
Nancy Heard-Costa
David Meyre
Andres Metspalu
Andre Uitterlinden
CAPS, CAHRES
Nabila Boutia-Naji
Amri
Nelis
Carola Zillikens
Erik Ingelsson
Essen Obesity Study
Tonu Esko
Cornelia van Duijn
CHS
Johannes Hebebrand
Samuli
Ripatti
Fernando Rivadineira
Talin Haritunians
Andre Scherag
Brenda Penninx
Karol Estrada
Robert Kaplan
Anke Hinney
Nicole Vogelzangs
Nicole Glazer
Tim Zandbelt
Marjo-Riita Jarvelin
GERMIFS
CONSORTIUM
Dorret Boomsma
Jeanette Erdmann
(expansion)
Jouke-Jan Hottenga
Michael Preuss
N= 129,000: 180 associated loci
~10% of heritability accounted for
Associated loci are strongly enriched for genes known
to underlie syndromes of abnormal skeletal growth
(“OMIM genes”)
Many loci with at least one reasonable candidate gene
Biology relevant to growth plate/cartilage
Many loci with no obvious candidate genes
Lango-Allen et al.
Nature 2010
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5/15/2015
Increase sample size to ~330,000
GWAS STUDIES
EUROSPAN
QIMR
ACTG
(MICROS, ORCADES, RISC
ADVANCE
VIS, KORCULA,)
RUNMC
BLSA
Fenland
SARDINIA
BRIGHT
FINGESTURE
SEARCH
BSN
FUSION
SHIP
CAPS
GASP
SORBS
CAHRES
GerMiFS
TRAILS
CGEMS
HealthABC
TWINGENE
(NHS, PLCO)
HERITAGE
Twins UK
CHARGE
HYPERGENES
TYROL
(AGES, Amish, ARIC,
WGHS
FHS, FRAM, RS1, RS II) InCHIANTI
IPM
WTCCC
CHS
KORA
UKBS
CNRS/ICL
LifeLines
HTN
CoLaus
Leiden Longevity
1958BC
COROGENE
LOLIPOP
YFS
deCODE
MGS
DESIR
MIGen
DGI
NBS
EGCUT
NELSON
EPIC
CONSORTIUM
NSPHS
DNBC
PHASE
ENGAGE
PREVEND
(ERF, Finnish Twins,
PROCARDIS
GENMETS, NESDA,
PROSPER
NFBC, NTR)
METABOCHIP STUDIES
ADVANCE
PIVUS
AMC-PAS
SardiNIA
BC58
SCARFSHEEP
BHS
SWABIA
CARDIOGENICS Swedish Twin Registry
Desir
THISEAS
D2D2007
The TromsøStudy
DIAGEN
ULSAM
DILGOM
The Whitehall study
Dundee
WTCCC-T2D
EAS
EGCUT
Ely
EPIC-Norfolk
Fenland
FUSION Stage2
GLACIER
HNR
HUNT 2
IMPROVE
KORA S3
KORA S4
Leipzig
LURIC
MORGAM
NSHD
GIANT central analysts
Sonja
Berndt
Hana
Lango
Reedik
Mägi
Adam
Locke
Gudmar
Thorleifsson
Andre
Scherag
Jian'an
Luan
Andy R
Wood
Eleanor Tsegaselassie
Stefan
Wheeler Workalemahu Gustafsson
Joshua
Randall
Teresa
Ferreira
Damien
CroteauChonka
Sailaja
Vedantam
Zoltán
Kutalik
Michael
Weedon
Tõnu
Esko
Thomas
Winkler
Tove
Fall
Felix
Day
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5/15/2015
GIANT height working group
Goncalo Abecasis
Sonja Berndt
Dan Chasman
Audrey Chu
Karol Estrada
Tonu Esko
Tim Frayling
Joel Hirschhorn
Erik Ingelsson
Guillaume Lettre
Ken Lo
Jeff O’Connell
Tune Pers
Sailaja Vedantam
Peter Visscher
Michael Weedon
Andy Wood
Jian Yang
GIANT height GWAS round 3, N~250,000
424 loci, 697 signals at p<5x10-8
Enriched for OMIM genes, missense variants, eQTLs
697 variants explain 20% of height variation
Top 10,000 variants capture much of the predicted
contribution of common genetic variation
Andy Wood, Tonu Esko, Sailaja Vedantam, Jian Yang, Peter Visscher,
Tim Frayling for GIANT height group, Nature Genetics 2014
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Understand human biology
?
Does discovering more loci
lead to more biology?
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5/15/2015
Biological connections from
earlier height study (180 loci)
Hedgehog signalling
Appetite
regulation
GH/IGF-related
pathways
Extracellular
matrix
BMP/Noggin
pathways
TGF-beta
signalling
Raychaudhuri et al.
PLoS Genet 2009
(GRAIL)
Biological connections with 423 loci
Same as previous:
Collagen/extracellular matrix
IGF/GH signaling
TGF-beta signaling
BMP/Noggin
MORE
Hedgehog signaling
Chromatin
LOCI = MORE BIOLOGY
Many loci still have no known connection
to biology of human growth
New:
FGF signaling
WNT signaling
Osteoglycin
TWIST/RUNX2
NPR2/NPPC
Bone/cartilage development
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5/15/2015
Same approach for obesity (BMI)
Gudmar
Þorleifsson
Sailaja
Vedantham
Michael
Boehnke
Cristen
Willer
Lu
Qi
Unnur
Thorsteinsdottir
Erik
Ingelsson
Cecilia
Lindgren
Ines
Barroso
Sonja
Berndt
Keri
Monda
Liz
Speliotes
Iris
Heid
Goncalo
Abecasis
Mark
McCarthy
Heather
Stringham
Joel
Hirschhorn
CONSORTIUM
Jian’an
Luan
Kari
North
Ruth
Loos
GIANT BMI Working Group
•
•
•
•
•
•
•
•
•
•
•
•
•
Ruth Loos
Sailaja Vedantam
Felix Day
Sonja Berndt
Stefan Gustafsson
Adam Locke
Corey Powell
Bratati Kahali
Damien Croteau-Chonka
Thomas Winkler
Andre Scherag
Inês Barroso
Jacqui Beckmann
•
•
•
•
•
•
•
•
•
•
•
•
Tune Pers
Cecilia Lindgren
Anne Justice
Peter Visscher
Cristen Willer
Jian Yang,
Karen Mohlke
Kari North
Joel Hirschorn
Erik Ingelsson
Elizabeth Speliotes
Michael Boehnke
68
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5/15/2015
~100 loci associated with BMI
Few obviously recognizable genes
CONSORTIUM
Locke et al. for GIANT BMI group, Nature 2015
Biomedical research and human
disease
GWAS, etc.
(✔)
Disease/trait
associated
loci
?
Therapeutic
leads
Biological
insight
35
5/15/2015
DEPICT: Novel approach to highlight
biology from GWAS data
Data-driven Expression-Prioritized Integration for Complex Traits
Goals of DEPICT
1. Prioritize genes in associated loci
2. Identify enriched gene sets
3. Identify enriched tissues and cell
types
Tune Pers (Broad/Boston Children’s)
Juha Karjalainen (Groningen)
Lude Franke (Groningen)
Pers et al., Nature Comm. 2015
DEPICT applied to height GWAS highights
cartilage and related cell types
Chondrocytes
Mesenchymal
stem cells
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5/15/2015
Central nervous system is the most relevant
tissue for the BMI GWAS results
Hippocampus /
limbic system
Hypothalamus /
pituitary
Novel gene sets from BMI GWAS results
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5/15/2015
Novel gene sets from BMI GWAS results
Possible sites of action of topiramate
Glutamatergic signaling and synaptic plasticity implicated in appetite regulation
Jennings et al. Science 2013, Cunningham et al. Cell Metab. 2012, Liu et al. Neuron 2012
Biomedical research and
human disease
GWAS, etc.
(✔)
Disease/trait
associated
loci
(✔)
Therapeutic
leads
Biological
insight
38
5/15/2015
Time frame of translation is long
Cholesterol structure elucidated
38 years
2 Nobel Prizes
Disease gene identified for
familial hypercholesterolemia
21 years
1 Nobel Prize
4S trial/Statin therapy
What about prediction?
“Precision Medicine”
39
5/15/2015
We already do prediction
in medicine
Predicted adult
height
+
Genetic risk score and
incident coronary artery disease
Mega et al. Lancet 2015
40
5/15/2015
Comparing genetic risk score to
other cardiovascular risk factors
Risk Factor for MI
Hazard Ratio for
Top Quintile versus
Bottom Quintile
Genetic risk score
1.7
LDL cholesterol
2.1
Systolic blood pressure
1.7
Type 2 diabetes (Y/N)
2.0
Framingham risk score
3.2
Ripatti et al., Lancet 2010
Genetic risk score and benefit
from statin therapy
Mega et al. Lancet 2015
41
5/15/2015
Genetics and endocrine diseases:
Summary
• Most diseases have genetic causes
• A small fraction of disease is due largely to rare
variants in single genes
– Often hard to recognize
– Can be diagnosed with sequencing
– Targeted if suggestive features, consider exome
• These sometimes should alter clinical care
– Leptin deficiency, MEN, MODY, etc.
– Comorbidities in syndromes
– Perhaps response to interventions
• Genetics of polygenic traits uncovers useful biology
– Impact is more long term, less in predictive power
Acknowledgements
Current or Past Children’s Hospital/Broad
Heather Carmichael
Andrew Dauber (Cincinnati)
Tonu Esko
Michael Guo
Guillaume Lettre (MHI)
Tim Miller
NIDDK, NICHD,
Jey Moon
March of Dimes,
Tune Pers
funders of GIANT
Jason Safer
cohorts
Rany Salem
Liz Speliotes (Michigan)
Jon Swartz
Vidhu Thaker
Sailaja Vedantam
CONSORTIUM
Sophie Wang
Short Stature
Ron Rosenfeld
Vivian Hwa
GIANT Consortium
BMI, height groups
Tim Frayling
Ruth Loos
DEPICT
Rudolf Fehrmann
Lude Franke
Juha Karjalainen
ACAN
Jeff Baron
Nancy Dunbar
Daniel Flynn
Christina Jacobsen
Julian Lui
Ola Nilsson
Jadranka Popovic
Fucosylation
Altan Ercan
Pieter Jacobs
Peter Nigrovic
Robert Sackstein
42